1. Field of the Invention
The present invention relates to a system and method for processing a large scale graph using GPUs, and more particularly, to a system and method capable of processing larger-scale graph data beyond the capacity of GPU device memory using a streaming method.
2. Discussion of Related Art
A graph processing system using GPUs can process a graph algorithm at a higher speed than a speed of a CPU by using GPUs having a higher throughput than the CPU.
A method of processing graph data having a scale that can be stored in a device memory mounted on a GPU has been proposed in a graph processing system using GPUs in the related art.
When the graph data having a scale that can be stored in the device memory is processed, there is an advantage that processing can be performed at a higher speed due to the high throughput of the GPU, unlike the CPU.
However, when a larger-scale graph beyond the capacity of GPU device memory is processed, the graph is divided into a part that can be stored in a GPU memory and a part that can be stored in a main memory.
Only the graph on the GPU memory is processed by the GPU, and the other graph on the main memory is processed by the CPU. Accordingly, as the scale of the graph becomes larger, it causes a problem in that degradation of performance.
Further, for graph data, when the numbers of partitions divided due to the increasing number of GPUs increases, duplication of data among the GPUs increases, and thus, graph processing performance is degraded. That is, scalability according to the increasing number of GPUs is not good.
Thus, importance of the method of processing large-scale graph data has been recognized, but research and technology development for a method for solving these technical problems have not been performed.